460 citations · 518 across the 7 of their papers we have counts for
7 papers
Multi-Objective Congestion Control
Yiqing Ma, Han Tian, Xudong Liao +4
Decades of research on Internet congestion control (CC) has produced a plethora of algorithms that optimize for different performance objectives. Applications face the challenge of…
Domain-specific Communication Optimization for Distributed DNN Training
Hao Wang, Jingrong Chen, Xinchen Wan +7
Communication overhead poses an important obstacle to distributed DNN training and draws increasing attention in recent years. Despite continuous efforts, prior solutions such as g…
FPGA-Based Hardware Accelerator of Homomorphic Encryption for Efficient Federated Learning
Zhaoxiong Yang, Shuihai Hu, Kai Chen
With the increasing awareness of privacy protection and data fragmentation problem, federated learning has been emerging as a new paradigm of machine learning. Federated learning t…
Quantifying the Performance of Federated Transfer Learning
Qinghe Jing, Weiyan Wang, Junxue Zhang +2
The scarcity of data and isolated data islands encourage different organizations to share data with each other to train machine learning models. However, there are increasing conce…
Secure Federated Matrix Factorization
Di Chai, Leye Wang, Kai Chen +1
To protect user privacy and meet law regulations, federated (machine) learning is obtaining vast interests in recent years. The key principle of federated learning is training a ma…
Enabling Work-conserving Bandwidth Guarantees for Multi-tenant Datacenters via Dynamic Tenant-Queue Binding
Zhuotao Liu, Kai Chen, Haitao Wu +4
Today's cloud networks are shared among many tenants. Bandwidth guarantees and work conservation are two key properties to ensure predictable performance for tenant applications an…